Bringing the Singularity Closer

Designing single purpose machines is relatively easier than generalized AI.

One-Dimensional Talents

IBM’s Watson machine, in its Jeopardy playing mode,
was never designed to be a “fully rounded individual”.

Because Watson was designed for a particular goal,
it is easy (in retrospect) for people to accept that it would excel at the
‘1-dimensional task’ that it was built for. After the initial euphoria of success,
the audience readily placed it on the same spectrum of clever/smart machines on which
computer chess Grandmasters had already been assigned a spot.

Humans are faced with a very nebulous task ahead when building a generalized AI.
In contrast, the task of building bigger, more powerful or more efficient machines
sounds like something that could be characterised as a ‘1-dimensional task’. Given the available precedents,
it’s relatively easy to accept that creating a machine that could do this specific task
better than the best available human is a practical goal. After all,
humans already have to use computer assistance to build microprocessors.

Simple proposal : Create a Watson that is good at designing better Watsons.

When does the Singularity Arrive?

Humans may not be able to design AIs - but the singularity doesn’t have to wait until we can.
We can accelerate pace of development by building a better developer first.

The singularity may be closer than it first appears : It doesn’t happen
when we can surpass an average human’s generalized intelligence. The singularity occurs when
there’s a machine-designing Watson that can design its own successor (and financiers are willing to invest in its designs).